Lessons learned: Semester I halfway done
My study at Computer Science Master Program, FMIPA IPB is halfway done. UTS (Mid Semester Tests) just finished. Many papers (assignments) need to be submitted, etc. I learned one thing very important about grad school. What is it?
It is that "Brilliance alone is not enough. One has to work hard!". It is very true. Take my words! 
This can also mean... Lack of sleep.
On earlier post I mentioned that I took three subjects this semester:
Here I lilke to outline the content of each subject so that you get the idea on what I've been thru (going thru) this semester. I won't outline the System Analysis & Design, cos its basically things that I've talked a lot during the last few years in this blog. It's the SDLC stuff, Object-Orientation, Design Patterns, etc. You have the idea. So, I'd like to highlight only the first two:
Algorithm Analysis & Design
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Review of Mathematical Foundations (Mathematical Logic, Algebra, Calculus (Function, Limit, Differential, Integral), Sequence, Proof Techniques, Combinatorics, Probability, Graph, etc).
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Criteria of "Good" Algorithm (Correctness, Amount of work done (Time), Amount of space needed, Simplicity, Optimality).
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Asymptotic Analysis / Complexity Analysis (Big O, Big Theta, Big Omega, Little O, Little Omega).
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Recurrence Relations.
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Algorithm Design Technique - Divide & Conquer, Dynamic Programming
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Algorithm Design Technique - Greedy, Recursive Backtracking
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Algorithms - Graph Algorithms, Approximation Algorithms, etc
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NP-Complete Theory --> BOOYAH!!
Mathematics & Statistics for Computing
One may think that this subject studies stuff like in Discrete Mathematics (Set Theory, Logic and Propositional Calculus, Relations & Functions, Linear Algebra, Combinatorics, Graph Theory, Probability Theory, Algebraic Systems, Boolean Algebra, Languages & Automata, Number Theory). It is true for undergrad studies. But in the subject that I took, all these materials in Discrete Mathematics are assumed to be mastered already. So, the subject consists of:
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Random Variable
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Multivariate Random Variable
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Markov Chain
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Hidden Markov Model
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Multivariate Analysis
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Fuzzy Theory - Fuzzy Set & Fuzzy Logic
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Rough Set
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Fourier Analysis
Semester II will starts within less than two months. There will be four subjects below that I will take:
Another fun ride awaits!
O, I also got a mentor for my thesis. She is Dr. Sri Nurdiati. Currently the Department Head of Computer Science IPB. She also teaches at the Department of Mathematics as her Ph.D is in Applied Mathematics. I have discussed with her on my plan to do thesis in Theory (Mathematical foundations of Computer Science) or in Computational Mathematics. Either way, as long as it is densed with Mathematics.